Smartphone-based sensor networks and some statistical

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Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Smartphone-based sensor networks and somestatistical challenges: the Earthquake Network

Android application

Francesco Finazzi

University of Bergamo

29 November 2013 - University of Glasgow

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Outline

Outline

Monitoring networks

Wireless sensor networks

Smartphone-based sensor networks (SSN)

Analysis of SSN data

Earthquake Network Android application

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Classic monitoring networks

Classic (wired) monitoring networks

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Monitoring network node

Monitoring network node

Byres Road - Scottish air quality network

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Monitoring network node

Air quality monitoring network

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Wireless sensor network

Wireless sensor network

Volcano monitoring - Harvard Sensor Networks Lab

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Smartphone-based sensor networks

Smartphone-based sensor network (SSN)

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Smartphones as nodes

Can we use smartphones?

Data transferGSM signal - not easy to have in remote areas

PowerExternal batteries, solar panels

Sensing capabilitiesAcceleration, geomagnetic �eld, temperature, illuminance,sound pressure, atm. pressure and humidityVisible light (camera)Position

Sensor accuracy and calibrationNot always good

GeolocationGPS or GSM signal

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Smartphones as nodes

Can we use smartphones?

Data transferGSM signal - not easy to have in remote areas

PowerExternal batteries, solar panels

Sensing capabilitiesAcceleration, geomagnetic �eld, temperature, illuminance,sound pressure, atm. pressure and humidityVisible light (camera)Position

Sensor accuracy and calibrationNot always good

GeolocationGPS or GSM signal

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Smartphones as nodes

Can we use smartphones?

Data transferGSM signal - not easy to have in remote areas

PowerExternal batteries, solar panels

Sensing capabilitiesAcceleration, geomagnetic �eld, temperature, illuminance,sound pressure, atm. pressure and humidityVisible light (camera)Position

Sensor accuracy and calibrationNot always good

GeolocationGPS or GSM signal

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Smartphones as nodes

Can we use smartphones?

Data transferGSM signal - not easy to have in remote areas

PowerExternal batteries, solar panels

Sensing capabilitiesAcceleration, geomagnetic �eld, temperature, illuminance,sound pressure, atm. pressure and humidityVisible light (camera)Position

Sensor accuracy and calibrationNot always good

GeolocationGPS or GSM signal

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Smartphones as nodes

Can we use smartphones?

Data transferGSM signal - not easy to have in remote areas

PowerExternal batteries, solar panels

Sensing capabilitiesAcceleration, geomagnetic �eld, temperature, illuminance,sound pressure, atm. pressure and humidityVisible light (camera)Position

Sensor accuracy and calibrationNot always good

GeolocationGPS or GSM signal

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Smartphones as nodes

Can we use smartphones?

Data transferGSM signal - not easy to have in remote areas

PowerExternal batteries, solar panels

Sensing capabilitiesAcceleration, geomagnetic �eld, temperature, illuminance,sound pressure, atm. pressure and humidityVisible light (camera)Position

Sensor accuracy and calibrationNot always good

GeolocationGPS or GSM signal

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Smartphones as nodes

Can we use smartphones?

Data transferGSM signal - not easy to have in remote areas

PowerExternal batteries, solar panels

Sensing capabilitiesAcceleration, geomagnetic �eld, temperature, illuminance,sound pressure, atm. pressure and humidityVisible light (camera)Position

Sensor accuracy and calibrationNot always good

GeolocationGPS or GSM signal

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Smartphones as nodes

Can we use smartphones?

Data transferGSM signal - not easy to have in remote areas

PowerExternal batteries, solar panels

Sensing capabilitiesAcceleration, geomagnetic �eld, temperature, illuminance,sound pressure, atm. pressure and humidityVisible light (camera)Position

Sensor accuracy and calibrationNot always good

GeolocationGPS or GSM signal

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Smartphones as nodes

Can we use smartphones?

Data transferGSM signal - not easy to have in remote areas

PowerExternal batteries, solar panels

Sensing capabilitiesAcceleration, geomagnetic �eld, temperature, illuminance,sound pressure, atm. pressure and humidityVisible light (camera)Position

Sensor accuracy and calibrationNot always good

GeolocationGPS or GSM signal

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Smartphones as nodes

Can we use smartphones?

Data transferGSM signal - not easy to have in remote areas

PowerExternal batteries, solar panels

Sensing capabilitiesAcceleration, geomagnetic �eld, temperature, illuminance,sound pressure, atm. pressure and humidityVisible light (camera)Position

Sensor accuracy and calibrationNot always good

GeolocationGPS or GSM signal

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Smartphones as nodes

Can we use smartphones?

Data transferGSM signal - not easy to have in remote areas

PowerExternal batteries, solar panels

Sensing capabilitiesAcceleration, geomagnetic �eld, temperature, illuminance,sound pressure, atm. pressure and humidityVisible light (camera)Position

Sensor accuracy and calibrationNot always good

GeolocationGPS or GSM signal

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Smartphones as nodes

Can we use smartphones?

Data transferGSM signal - not easy to have in remote areas

PowerExternal batteries, solar panels

Sensing capabilitiesAcceleration, geomagnetic �eld, temperature, illuminance,sound pressure, atm. pressure and humidityVisible light (camera)Position

Sensor accuracy and calibrationNot always good

GeolocationGPS or GSM signal

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Smartphones as nodes

SSN applications

Environmental �eld estimation

Temperature, pressure, humidity,...

Earthquakes (accelerometer)

Avalanches/landslides (microphone)

Air quality (camera+�lter)

Fire/smoke detection (camera)

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Smartphones as nodes

SSN applications

Environmental �eld estimation

Temperature, pressure, humidity,...

Earthquakes (accelerometer)

Avalanches/landslides (microphone)

Air quality (camera+�lter)

Fire/smoke detection (camera)

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Smartphones as nodes

SSN applications

Environmental �eld estimation

Temperature, pressure, humidity,...

Earthquakes (accelerometer)

Avalanches/landslides (microphone)

Air quality (camera+�lter)

Fire/smoke detection (camera)

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Smartphones as nodes

SSN applications

Environmental �eld estimation

Temperature, pressure, humidity,...

Earthquakes (accelerometer)

Avalanches/landslides (microphone)

Air quality (camera+�lter)

Fire/smoke detection (camera)

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Smartphones as nodes

SSN applications

Environmental �eld estimation

Temperature, pressure, humidity,...

Earthquakes (accelerometer)

Avalanches/landslides (microphone)

Air quality (camera+�lter)

Fire/smoke detection (camera)

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Smartphones as nodes

SSN applications

Environmental �eld estimation

Temperature, pressure, humidity,...

Earthquakes (accelerometer)

Avalanches/landslides (microphone)

Air quality (camera+�lter)

Fire/smoke detection (camera)

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

SSN types

SSN types

Private SSNs - Sensor network with smartphones as nodes.The network is operated by a network manager which isresponsible for buying, installing and maintaining the nodes.

Public SSNs - Sensor network based on smartphonesbelonging to their single owners. The smartphone is part ofthe network only if the owner agrees to be part of it.

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

SSN types

SSN types

Private SSNs - Sensor network with smartphones as nodes.The network is operated by a network manager which isresponsible for buying, installing and maintaining the nodes.

Public SSNs - Sensor network based on smartphonesbelonging to their single owners. The smartphone is part ofthe network only if the owner agrees to be part of it.

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Public SSNs

Public SSNs architecture

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Public SSNs

Public SSNs

Dynamic network: the total number of nodes, the number ofactive nodes and the location of the nodes changecontinuously;

Location is not always known precisely (can we usenon-localized smartphones?);

Heterogeneous nodes: di¤erent vendors and models;

Sensors are often uncalibrated;

Asynchronous data acquisition;

Preferential sampling (remote areas?);

Someone else pays device and energy.

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Public SSNs

Public SSNs

Dynamic network: the total number of nodes, the number ofactive nodes and the location of the nodes changecontinuously;

Location is not always known precisely (can we usenon-localized smartphones?);

Heterogeneous nodes: di¤erent vendors and models;

Sensors are often uncalibrated;

Asynchronous data acquisition;

Preferential sampling (remote areas?);

Someone else pays device and energy.

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Public SSNs

Public SSNs

Dynamic network: the total number of nodes, the number ofactive nodes and the location of the nodes changecontinuously;

Location is not always known precisely (can we usenon-localized smartphones?);

Heterogeneous nodes: di¤erent vendors and models;

Sensors are often uncalibrated;

Asynchronous data acquisition;

Preferential sampling (remote areas?);

Someone else pays device and energy.

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Public SSNs

Public SSNs

Dynamic network: the total number of nodes, the number ofactive nodes and the location of the nodes changecontinuously;

Location is not always known precisely (can we usenon-localized smartphones?);

Heterogeneous nodes: di¤erent vendors and models;

Sensors are often uncalibrated;

Asynchronous data acquisition;

Preferential sampling (remote areas?);

Someone else pays device and energy.

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Public SSNs

Public SSNs

Dynamic network: the total number of nodes, the number ofactive nodes and the location of the nodes changecontinuously;

Location is not always known precisely (can we usenon-localized smartphones?);

Heterogeneous nodes: di¤erent vendors and models;

Sensors are often uncalibrated;

Asynchronous data acquisition;

Preferential sampling (remote areas?);

Someone else pays device and energy.

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Public SSNs

Public SSNs

Dynamic network: the total number of nodes, the number ofactive nodes and the location of the nodes changecontinuously;

Location is not always known precisely (can we usenon-localized smartphones?);

Heterogeneous nodes: di¤erent vendors and models;

Sensors are often uncalibrated;

Asynchronous data acquisition;

Preferential sampling (remote areas?);

Someone else pays device and energy.

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Public SSNs

Public SSNs

Dynamic network: the total number of nodes, the number ofactive nodes and the location of the nodes changecontinuously;

Location is not always known precisely (can we usenon-localized smartphones?);

Heterogeneous nodes: di¤erent vendors and models;

Sensors are often uncalibrated;

Asynchronous data acquisition;

Preferential sampling (remote areas?);

Someone else pays device and energy.

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

SSN data analysis

SSN data analysis

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Classic monitoring network - Data matrix

Classic monitoring network - Data matrix

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Classic monitoring network - Data matrix

SSN - Geolocation

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Classic monitoring network - Data matrix

Dynamic network

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Classic monitoring network - Data matrix

Dynamic network

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Classic monitoring network - Data matrix

SSN - Data table

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Calibration

Sensor calibration

Smartphone sensors are often uncalibrated or...

they require periodic calibration

Manual calibration is not easy/practicable

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Calibration

"On the �y" calibration based on geofence

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Calibration

Calibration curve

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Introduction

Earthquake Network Android app

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Earthquake Network as SSN

Earthquake Network

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Earthquake Network as SSN

Earthquake Network

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Why and what

Why and what

Why detect quakes?

O¢ cial networks take between 15 and 60 minutes to notifyPopulation noti�cationIntensity (shake map)

What can be detected?

Time of the eventIntensityEpicenter (not easy)

What cannot be detected?

Magnitude (energy)

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Why and what

Why and what

Why detect quakes?

O¢ cial networks take between 15 and 60 minutes to notifyPopulation noti�cationIntensity (shake map)

What can be detected?

Time of the eventIntensityEpicenter (not easy)

What cannot be detected?

Magnitude (energy)

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Why and what

Why and what

Why detect quakes?

O¢ cial networks take between 15 and 60 minutes to notifyPopulation noti�cationIntensity (shake map)

What can be detected?

Time of the eventIntensityEpicenter (not easy)

What cannot be detected?

Magnitude (energy)

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Why and what

Why and what

Why detect quakes?

O¢ cial networks take between 15 and 60 minutes to notifyPopulation noti�cationIntensity (shake map)

What can be detected?

Time of the eventIntensityEpicenter (not easy)

What cannot be detected?

Magnitude (energy)

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Why and what

Why and what

Why detect quakes?

O¢ cial networks take between 15 and 60 minutes to notifyPopulation noti�cationIntensity (shake map)

What can be detected?

Time of the eventIntensityEpicenter (not easy)

What cannot be detected?

Magnitude (energy)

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Why and what

Why and what

Why detect quakes?

O¢ cial networks take between 15 and 60 minutes to notifyPopulation noti�cationIntensity (shake map)

What can be detected?

Time of the eventIntensityEpicenter (not easy)

What cannot be detected?

Magnitude (energy)

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Why and what

Why and what

Why detect quakes?

O¢ cial networks take between 15 and 60 minutes to notifyPopulation noti�cationIntensity (shake map)

What can be detected?

Time of the eventIntensityEpicenter (not easy)

What cannot be detected?

Magnitude (energy)

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Why and what

Why and what

Why detect quakes?

O¢ cial networks take between 15 and 60 minutes to notifyPopulation noti�cationIntensity (shake map)

What can be detected?

Time of the eventIntensityEpicenter (not easy)

What cannot be detected?

Magnitude (energy)

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Why and what

Why and what

Why detect quakes?

O¢ cial networks take between 15 and 60 minutes to notifyPopulation noti�cationIntensity (shake map)

What can be detected?

Time of the eventIntensityEpicenter (not easy)

What cannot be detected?

Magnitude (energy)

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Why and what

Why and what

Why detect quakes?

O¢ cial networks take between 15 and 60 minutes to notifyPopulation noti�cationIntensity (shake map)

What can be detected?

Time of the eventIntensityEpicenter (not easy)

What cannot be detected?

Magnitude (energy)

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

HW/SW architecture

HW/SW architecture

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

HW/SW architecture

HW/SW architecture

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

SW architecture

App dashboard

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Vibrations and quakes

Vibration vs earthquake

Vibration: smartphone movement

Earthquake: waves of energy travelling through the Earth�slayers

Smartphones measure vibrations, the network measuresearthquakes

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Vibrations and quakes

Vibration vs earthquake

Vibration: smartphone movement

Earthquake: waves of energy travelling through the Earth�slayers

Smartphones measure vibrations, the network measuresearthquakes

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Vibrations and quakes

Vibration vs earthquake

Vibration: smartphone movement

Earthquake: waves of energy travelling through the Earth�slayers

Smartphones measure vibrations, the network measuresearthquakes

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Vibration detection

Vibration detection

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Accelerometer calibration

Accelerometer calibration

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Vibration detection

Vibration detection - Battery charging

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Earthquake detection

Earthquake detection

(non geolocalized smartphones?)

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Dynamic network

Active nodes

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Dynamic network

Active nodes

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Earthquake Network

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Dynamic network

Active nodes

Downloads: � 270000 (11 months)Total active users: � 30000Active nodes at any time: � 10000Enabled nodes at any time: 100� 250 (3%� 8%)3% of 1.4 billion (potential) smartphones is a large number

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Dynamic network

Active nodes

Downloads: � 270000 (11 months)Total active users: � 30000Active nodes at any time: � 10000Enabled nodes at any time: 100� 250 (3%� 8%)3% of 1.4 billion (potential) smartphones is a large number

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Dynamic network

Active nodes

Downloads: � 270000 (11 months)Total active users: � 30000Active nodes at any time: � 10000Enabled nodes at any time: 100� 250 (3%� 8%)3% of 1.4 billion (potential) smartphones is a large number

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Dynamic network

Active nodes

Downloads: � 270000 (11 months)Total active users: � 30000Active nodes at any time: � 10000Enabled nodes at any time: 100� 250 (3%� 8%)3% of 1.4 billion (potential) smartphones is a large number

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Dynamic network

Active nodes

Downloads: � 270000 (11 months)Total active users: � 30000Active nodes at any time: � 10000Enabled nodes at any time: 100� 250 (3%� 8%)3% of 1.4 billion (potential) smartphones is a large number

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Conclusions

Conclusions

Environmental sensors are becoming available for o¤-the-shelfproducts

Smartphones are the natural candidates to carry aroundsensors

However:

A SSN should be based on a large number of smartphones(not easy)Calibrations of heterogeneous sensors can be an issueStatistical methods/software for SSN space-time data may notbe immediately available

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Conclusions

Conclusions

Environmental sensors are becoming available for o¤-the-shelfproducts

Smartphones are the natural candidates to carry aroundsensors

However:

A SSN should be based on a large number of smartphones(not easy)Calibrations of heterogeneous sensors can be an issueStatistical methods/software for SSN space-time data may notbe immediately available

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Conclusions

Conclusions

Environmental sensors are becoming available for o¤-the-shelfproducts

Smartphones are the natural candidates to carry aroundsensors

However:

A SSN should be based on a large number of smartphones(not easy)Calibrations of heterogeneous sensors can be an issueStatistical methods/software for SSN space-time data may notbe immediately available

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Conclusions

Conclusions

Environmental sensors are becoming available for o¤-the-shelfproducts

Smartphones are the natural candidates to carry aroundsensors

However:

A SSN should be based on a large number of smartphones(not easy)Calibrations of heterogeneous sensors can be an issueStatistical methods/software for SSN space-time data may notbe immediately available

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Conclusions

Conclusions

Environmental sensors are becoming available for o¤-the-shelfproducts

Smartphones are the natural candidates to carry aroundsensors

However:

A SSN should be based on a large number of smartphones(not easy)Calibrations of heterogeneous sensors can be an issueStatistical methods/software for SSN space-time data may notbe immediately available

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

Conclusions

Conclusions

Environmental sensors are becoming available for o¤-the-shelfproducts

Smartphones are the natural candidates to carry aroundsensors

However:

A SSN should be based on a large number of smartphones(not easy)Calibrations of heterogeneous sensors can be an issueStatistical methods/software for SSN space-time data may notbe immediately available

Introduction Monitoring networks WSN SSN SSN data analysis Earthquake Network Conclusions

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